Cross-variant comparison of all registers read by tools/mmio-probe/probe.sh.
15 Ampere cards probed: 2× CMP 170HX 10GB (Cab + Own physical hardware, 2026-05-05/07) + 11 via Vast.ai rentals + 2× Drive A100 32GB (PG199, GA100-550F-A1, physical hardware, 2026-05-31).
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Most of the source comes from: Steam Beta Forum
Thank you so much to everyone in the forum for contributing, for reaching out to 8BitDo to request switching between XInput/DInput/Switch mode on the dongle, to Valve for adding support on DInput mode, to the SDL developers (and 8bitdo) for adding support on DInput mode, and finally, to the Linux kernel developers for adding support on XInput mode.
This gist summarizes everything from that forum.
So after the latest firmware update (as the time of writing: Controller 1.06, Adapter 1.04), its now possible to switch to DInput and Switch mode by holding B (DInput) or Y (Switch) while turning on t
| { | |
| "name": "Portfolio 1: Invoice manager", | |
| "nodes": [ | |
| { | |
| "parameters": { | |
| "pollTimes": { | |
| "item": [ | |
| { | |
| "mode": "everyMinute" | |
| } |
| /* | |
| Based on Cassidy’s CSS tweaks for mastodon.blaede.family (https://gist.github.com/cassidyjames/292c1e3062ad5248284999e4c7841a17) | |
| Inspired in part by TangerineUI: | |
| https://github.com/nileane/TangerineUI-for-Mastodon/ | |
| …but much smaller in scope. | |
| Simplified-to-only-keep-color by @eramdam@erambert.me. | |
| */ | |
| /* MAIN ACCENT COLORS. */ |
Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
- Follow standard conventions.
- Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
- Boy scout rule. Leave the campground cleaner than you found it.
- Always find root cause. Always look for the root cause of a problem.
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.